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[Fully funded studentship partially funded by NERC, includes a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant (RTSG) of £8,000. International candidates may be eligible for full fee coverage subject to UKRI rules.] This fully funded PhD studentship at Loughborough University offers an exciting opportunity to advance research in environmental monitoring by optimising aerial image analysis for beach litter characterisation and quantification. The project is embedded within a three-year marine litter monitoring campaign on the Isle of Skye, Scotland, and builds on the university’s extensive research in this area, including the '50 Years of Litter on Skye' initiative. The successful candidate will join an interdisciplinary team integrating environmental science, engineering, and social science methodologies, working closely with community partners across Scotland’s west coast. The research will focus on evaluating the efficacy and suitability of digital image collection and analysis for characterising beach litter on heavily-littered coastlines. The project will assess various image capture techniques, including the use of drones and mobile phones, and explore the potential of different sensor types such as RGB and multispectral cameras. The analysis will compare manual digital approaches (e.g., Dot Dot Goose) with the development of automated computer vision algorithms for marine litter characterisation and quantification. Supervision will be provided by Dr Tom Stanton (primary), Prof. Cunjia Liu, Prof. Adrian Spencer, and Dr Nicholas Midgley (Nottingham Trent University), offering a breadth of expertise in environmental science, engineering, and computational methods. The studentship is partially funded by NERC and provides a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant (RTSG) of £8,000. International candidates are eligible, with the university covering the difference between UK and international tuition fees for successful applicants, subject to UKRI funding rules. Applicants should hold or expect to obtain at least a 2:1 degree (or equivalent) in Geography, Environmental Science, Computer Science, Engineering, or a related field, or possess an appropriate Master’s degree. Minimum English language requirements apply. The application process involves completing a CENTA studentship application form (available at https://centa.ac.uk/apply/ ) and submitting it online via the Loughborough University portal, selecting the 'Department of Geography and Environment' and quoting reference CENTA2026-LU09. The deadline for applications is January 7th, 2026, with interviews expected in early February 2026. This studentship is ideal for candidates interested in interdisciplinary research at the intersection of environmental science, computer vision, and community engagement, with a strong commitment to addressing marine litter challenges through innovative technological solutions.

This PhD project at Loughborough University aims to optimise aerial image analysis for the characterisation and quantification of beach litter, building on the university’s extensive research into marine litter, including the '50 Years of Litter on Skye' initiative. The research responds to a three-year marine litter monitoring campaign on the Isle of Skye and involves collaboration with community partners across Scotland’s west coast. The project is highly interdisciplinary, integrating environmental science, engineering, and community science methodologies. The successful candidate will evaluate the efficacy and suitability of digital image collection and analysis for beach litter characterisation, focusing on heavily-littered coastlines. The research will assess the practicality of various image capture techniques, including the use of drones and mobile phones, and explore the potential of different sensor types such as RGB and multispectral sensors. Image analysis will involve both manual digital approaches (e.g., Dot Dot Goose) and the development of automated computer vision algorithms for marine litter characterisation and quantification. The project is designed to enhance marine litter monitoring methods and support community-led environmental initiatives. The studentship is partially funded by NERC and provides a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant of £8,000. International candidates are eligible, with the university covering the difference between UK and international tuition fees for successful applicants, subject to UKRI funding rules. Applicants should have at least a 2:1 degree (or equivalent) in a relevant field such as Geography, Environmental Science, Computer Science, or Engineering, and must meet the university’s English language requirements. The position is available full-time (3.5 years) or part-time (7 years), with a start date in October 2026. Applications close on January 7th, 2026, and interviews for shortlisted candidates will be held in February 2026. For application instructions, candidates should complete the CENTA studentship application form and apply online, quoting the reference number CENTA2026-LU09.

[Fully funded studentship, partially funded by NERC, includes a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant (RTSG) of £8,000. International candidates may be eligible for fee support to cover the difference between UK and International tuition fees, subject to UKRI rules (max 30% international studentships).] This fully funded PhD studentship at Loughborough University focuses on optimising aerial image analysis for the characterisation and quantification of beach litter, building on the university’s extensive research into marine litter on the Isle of Skye and Scotland’s west coast. The project is part of a three-year marine litter monitoring campaign and involves close collaboration with community partners. The research will evaluate the effectiveness of digital image collection and analysis methods, including the use of drones and mobile phones, to monitor heavily-littered coastlines. It will assess various image capture techniques and sensor types (such as RGB and multispectral) to generate high-quality beach litter images. The analysis will compare manual digital approaches (e.g., Dot Dot Goose) with the development of automated computer vision algorithms for marine litter characterisation and quantification. The interdisciplinary nature of the project requires integrating environmental science, engineering, and community science methodologies. The successful candidate will join a team of researchers and work with community groups to advance practical solutions for marine litter monitoring. Funding is provided through NERC and includes a tax-free stipend of £20,780 per annum (2025/26), UK tuition fees for 3.5 years, and a Research Training Support Grant of £8,000. International candidates may be eligible for additional fee support, subject to UKRI rules. Applicants should have at least a 2:1 degree (or equivalent) in Geography, Environmental Science, Computer Science, Engineering, or a related field, and meet minimum English language requirements. Applications require a CENTA studentship application form, CV, and supporting documents, with a deadline of January 7th, 2026. Interviews for shortlisted candidates will be held in early February 2026.

The AIGreenBots EU Project, coordinated by Cristiano Premebida, is a prestigious MSCA Doctoral Network initiative focused on advancing AI and robotic technologies for agricultural applications. The project is recruiting 11 PhD positions across five countries, including a position at Loughborough University Centre for Autonomous Systems supervised by Professor Cunjia Liu. Research topics include robotic environment sensing, AI, machine learning, and sustainable agriculture. The programme offers multidisciplinary collaboration between academia and industry, secondments in non-academic partners, and excellent payment conditions. Applicants should have a background in computer science, engineering, robotics, or related fields, and be passionate about contributing to agricultural robotics. Application details and project information are available on the AIGreenBots website, with a deadline of August 1, 2024.